Exploring Topical Lead-Lag across Corpora

被引:12
|
作者
Liu, Shixia [1 ]
Chen, Yang [2 ]
Wei, Hao [3 ]
Yang, Jing [2 ]
Zhou, Kun [3 ]
Drucker, Steven M. [1 ]
机构
[1] Microsoft Res, Redmond, WA 98052 USA
[2] Univ N Carolina, Dept Comp Sci, Charlotte, NC 28223 USA
[3] Zhejiang Univ, Dept Comp Sci, Hangzhou, Zhejiang, Peoples R China
关键词
Text visualization; lead-lag analysis; tree visualization; adaptive focus plus context; TRACKING; DESIGN;
D O I
10.1109/TKDE.2014.2324581
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Identifying which text corpus leads in the context of a topic presents a great challenge of considerable interest to researchers. Recent research into lead-lag analysis has mainly focused on estimating the overall leads and lags between two corpora. However, real-world applications have a dire need to understand lead-lag patterns both globally and locally. In this paper, we introduce TextPioneer, an interactive visual analytics tool for investigating lead-lag across corpora from the global level to the local level. In particular, we extend an existing lead-lag analysis approach to derive two-level results. To convey multiple perspectives of the results, we have designed two visualizations, a novel hybrid tree visualization that couples a radial space-filling tree with a node-link diagram and a twisted-ladder-like visualization. We have applied our method to several corpora and the evaluation shows promise, especially in support of text comparison at different levels of detail.
引用
收藏
页码:115 / 129
页数:15
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